首页|Artificial intelligence for risk analysis-A risk characterization perspective on advances, opportunities, and limitations

Artificial intelligence for risk analysis-A risk characterization perspective on advances, opportunities, and limitations

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  • NETL
  • NSTL
  • Wiley
Artificial intelligence (AI) has seen numerous applications for risk analysis and providesample opportunities for developing new and improved methods and models forthis purpose. In the present article, we conceptualize the use of AI for risk analysisby framing it as an input–algorithm–output process and linking such a setup to threetasks in establishing a risk description: consequence characterization, uncertainty characterization,and knowledge management. We then give an overview of currently usedconcepts and methods for AI-based risk analysis and outline potential future uses byextrapolating beyond currently produced types of output. We end with a discussion ofthe limits of automation, both near-term limitations and a more fundamental questionrelated to allowing AI to automatically prescribe risk management decisions. We concludethat there are opportunities for using AI for risk analysis to a greater extent thanis commonly the case today; however, critical concerns about proper uncertainty representationand the need for risk-informed rather than risk-based decision-making alsolead us to conclude that risk analysis and decision-making processes cannot be fullyautomated.

artificial intelligencerisk analysis

Kaia Stødle、Roger Flage、Seth Guikema、Terje Aven

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Department of Safety, Economics and Planning,University of Stavanger, Stavanger, Norway

Department of Civil and EnvironmentalDepartment of Safety, Economics and Planning,University of Stavanger, Stavanger, Norway

Engineering and Department of Industrial &Operations Engineering, University of Michigan,Ann Arbor, Michigan, USA

2025

10.1111/risa.14307

Risk analysis

Risk analysis

ISSN：0272-4332
年,卷(期)：2025.45(4)
  • 102